Solder Joint Failure Modes in the Conventional Crystalline Si Module

Itoh, Uichi; Yoshida, Minoru; Tokuhisa, Hideo; Takeuchi, Kohichi; Takemura, Yasuyuki

doi:10.1016/j.egypro.2014.08.010

Cited by 40 publications

(15 citation statements)

References 3 publications

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“…18 This Ag leaching effect develops crack in the soldered interface due to thermal expansion resulting in connection break down. Juris Kalejs 17 raised concern regarding robustness and durability of junction boxes.…”

Section: General Faults In All Pv Modulesmentioning

confidence: 99%

“…This causes wiring failure which leads to internal arcing. Uichi Itoh et al 18 depicted the potential risks associated due to soldering failures in junction boxes. The observations depicted two different faults, ie silver (Ag) leaching and solder joint fatigue.…”

Section: General Faults In All Pv Modulesmentioning

confidence: 99%

“…When solder joints come in contact with the AG electrodes of solar cell, they get dissolved with the solder electrodes (Tin-Lead (Pb-Sn)) and is observed as Ag 3 Sn compound. 18 This Ag leaching effect develops crack in the soldered interface due to thermal expansion resulting in connection break down. Delamination effect occurs due to adhesion contamination or due to environmental factors as shown in Figure 5, which ingress humidity, moisture, and corrosion into the laminates of PV module.…”

Section: General Faults In All Pv Modulesmentioning

confidence: 99%

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Fault diagnosis of Photovoltaic Modules

Haque

Bharath

Khan

et al. 2019

Energy Science & Engineering

129

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Fault diagnosis and condition monitoring are important to increase the efficiency and reliability of photovoltaic modules. This paper reviews the challenges and limitations associated with fault diagnosis of solar modules. A thorough analysis of various faults responsible for failure of solar modules has been discussed. After reviewing relevant work, a monitoring tool is designed using thermography and artificial intelligent systems that allows the detection of various types of faults in PV modules and at the same time the designed tool aims to filter the nonsignificant anomalies. A neural network (NN) classifier is applied to the transfer characteristics (I‐V data) of the faulty PV module for the diagnosis which adapts multilayer perceptron (MLP) networks to identify the type and location of occurring faults. The Discrete wavelet transform (DWT) based signal processing technique is utilized in the feature extraction process to reduce the NN input size. The developed detection algorithm is adapted for 24/7 automated surveillance. For a given fault condition, the average fault detection time is observed to be <9 seconds, which is lower than the previous work done. The developed algorithm achieved 100% accuracy when tested on a predetermined fault data set.

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Section: General Faults In All Pv Modulesmentioning

confidence: 99%

Section: General Faults In All Pv Modulesmentioning

confidence: 99%

Section: General Faults In All Pv Modulesmentioning

confidence: 99%

See 1 more Smart Citation

Fault diagnosis of Photovoltaic Modules

Haque

Bharath

Khan

et al. 2019

Energy Science & Engineering

129

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show abstract

“…Remarkably, the on‐site infrared image in Figure B exhibits localized hot spots caused by solder bond failure, in accord with our deconvolution analysis of increased series resistance. It is generally known that solder bond failure is caused by the differential thermal expansion between the solder joints and surrounding materials during repeated thermal cycling . Therefore, solder bonds fail (crack) in a stepwise fashion .…”

Section: Application To Field Datamentioning

confidence: 99%

“…It is generally known that solder bond failure is caused by the differential thermal expansion between the solder joints and surrounding materials during repeated thermal cycling. 38,39 Therefore, solder bonds fail (crack) in a stepwise fashion. 40 Indeed, we find the signature of this stepwise increase in the series resistance in the Suns-Vmp analysis; see Figure 11A.…”

Section: Validation 4: Onsite Inspectionmentioning

confidence: 99%

Real‐time monitoring and diagnosis of photovoltaic system degradation only using maximum power point—the Suns‐Vmp method

Sun

Chavali

Alam

2018

Progress in Photovoltaics

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The uncertainties associated with technology‐specific and geography‐specific degradation rates make it difficult to calculate the levelized cost of energy, and thus the economic viability of solar energy. In this regard, millions of fielded photovoltaic modules may serve as a global testbed, where we can interpret the routinely collected time series maximum power point (MPP) data to assess the time‐dependent “health” of solar modules. The existing characterization methods, however, cannot effectively mine/decode these datasets to identify various degradation pathways. In this paper, we propose a new methodology called the Suns‐Vmp method, which offers a simple yet powerful approach to monitoring and diagnosing time‐dependent degradation of solar modules by using the MPP data. The algorithm reconstructs “IV” curves by using the natural illumination‐dependent and temperature‐dependent daily MPP characteristics as constraints to fit physics‐based circuit models. These synthetic IV characteristics are then used to determine the time‐dependent evolution of circuit parameters (eg, series resistance), which in turn allows one to deduce the dominant degradation modes (eg, solder bond failure) of solar modules. The proposed method has been applied to a test facility at the National Renewable Energy Laboratory. Our analysis indicates that the solar modules degraded at a rate of ~0.7%/year because of discoloration and weakened solder bonds. These conclusions are validated by independent outdoor IV measurements and on‐site imaging characterization. Integrated with physics‐based degradation models or machine learning algorithms, the method can also serve to predict the lifetime of photovoltaic systems.

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Overview and Impact of Faults in Grid‐Connected Photovoltaic Systems

Khan

2022

Fault Analysis and Its Impact on Grid‐connected Photovoltaic Systems Performance

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Solder Joint Failure Modes in the Conventional Crystalline Si Module

Cited by 40 publications

References 3 publications

Fault diagnosis of Photovoltaic Modules

Fault diagnosis of Photovoltaic Modules

Real‐time monitoring and diagnosis of photovoltaic system degradation only using maximum power point—the Suns‐Vmp method

Overview and Impact of Faults in Grid‐Connected Photovoltaic Systems

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